An Australian abroad : the secret life of the brushtail possum (Trichosurus vulpecula) : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Veterinary Science at Massey University, Manawatu, New Zealand

The “superspreader” hypothesis relates disease transmission to social contacts and assumes transmission is driven by the frequency, type and distribution of contacts among infected and susceptible individuals. I investigated characteristics of brushtail possum (Trichosurus vulpecula) home ranges for six wild free-living subpopulations, (four grids were studied; all of them before possum depopulation and two of them after possum depopulation) constructing social networks relevant to bovine tuberculosis (TB) transmission before and after depopulation. I also experimentally infected possums with a novel strain of TB to monitor secondary case infections in relation to these contact and other factors, including population density and sex ratio. Before depopulation home range estimates showed adult males had larger home ranges than female and younger possums. Home range overlap and area of overlap differed between subpopulations, and possum sex and age; with adult males having more and larger overlaps with other possums. Possums were fitted with proximity-logging collars and contacts registered between April and October, 2012. The number of connections an individual has with others and the probability of the distribution of contacts it has within the population, or node degree and betweenness, also known as the shortest distance between individuals, were associated with sex, with males having higher values for each. Males also contacted more possums than females. Post-depopulation results showed an influx of male possums, higher population density, and smaller home range sizes than before depopulation. Possums post-depopulation also lacked an apparent ‘routine’ in contact networks, interacting with other possums haphazardly. The greater level of contact among adult males, than before depopulation, and their effects on recovering populations post-depopulation, was likely the cause of more TB infection in adults and males. This thesis provides empirical evidence that adult male possums have home range and contact network characteristics that are likely to enhance their involvement in the transmission and persistence of TB, relative to female and younger possums. Observations of experimentally infected individuals showed that infected males survived longer than females and that, as a consequence, those males potentially acted as a “supershedding” subgroup. I therefore provide evidence that adult male possums are the most important drivers of TB transmission and persistence of infection in populations, and could be targeted for control measures

Function Assistant: A Tool for NL Querying of APIs

In this paper, we describe Function Assistant, a lightweight Python-based toolkit for querying and exploring source code repositories using natural language. The toolkit is designed to help end-users of a target API quickly find information about functions through high-level natural language queries and descriptions. For a given text query and background API, the tool finds candidate functions by performing a translation from the text to known representations in the API using the semantic parsing approach of Richardson and Kuhn (2017). Translations are automatically learned from example text-code pairs in example APIs. The toolkit includes features for building translation pipelines and query engines for arbitrary source code projects. To explore this last feature, we perform new experiments on 27 well-known Python projects hosted on Github.Comment: in Proceedings of EMNLP-2017 (system demonstrations

Learning Semantic Correspondences in Technical Documentation

We consider the problem of translating high-level textual descriptions to formal representations in technical documentation as part of an effort to model the meaning of such documentation. We focus specifically on the problem of learning translational correspondences between text descriptions and grounded representations in the target documentation, such as formal representation of functions or code templates. Our approach exploits the parallel nature of such documentation, or the tight coupling between high-level text and the low-level representations we aim to learn. Data is collected by mining technical documents for such parallel text-representation pairs, which we use to train a simple semantic parsing model. We report new baseline results on sixteen novel datasets, including the standard library documentation for nine popular programming languages across seven natural languages, and a small collection of Unix utility manuals.Comment: accepted to ACL-201

Polyglot Semantic Parsing in APIs

Traditional approaches to semantic parsing (SP) work by training individual models for each available parallel dataset of text-meaning pairs. In this paper, we explore the idea of polyglot semantic translation, or learning semantic parsing models that are trained on multiple datasets and natural languages. In particular, we focus on translating text to code signature representations using the software component datasets of Richardson and Kuhn (2017a,b). The advantage of such models is that they can be used for parsing a wide variety of input natural languages and output programming languages, or mixed input languages, using a single unified model. To facilitate modeling of this type, we develop a novel graph-based decoding framework that achieves state-of-the-art performance on the above datasets, and apply this method to two other benchmark SP tasks.Comment: accepted for NAACL-2018 (camera ready version

Collaborative Collective Algorithms to Coordinate UGVs

Sentel/Brilliant Innovations has developed autonomous UGVs (unmanned ground vehicles) capable of generating a map of an unknown location through exploration using local software and the power of Google Tango technology. This project was tasked with developing an efficient and capable map-stitching solution allowing multiple UGVs to coordinate their movements and share information in order to greatly improve the speed at which these drones can be used to generate maps. The solution utilizes the processing power of a Raspberry Pi to pull maps from a Redis server and stitch them together. Once stitched, the maps are redistributed via the Redis server back through the network, providing every UGV the opportunity to obtain the global map. All of this stitching is performed on a single UGV, freeing the other drones to focus on generating and uploading their own unique maps to the server. The drones can use this new information to better inform their next move to prevent multiple drones from generating a map of the same location. In the future, Sentel/Brilliant Innovations hopes to take this technology and attach more advanced sensors to the drones, allowing them to add greater detail of the environment to the map rather than simply drawing boundaries. These drones have many potential applications, such as search and rescue, seeking out potential hazards, and intelligence for military and civil use.https://scholarscompass.vcu.edu/capstone/1187/thumbnail.jp

Investigation into the role of pump to signal power ratio in FWM-based phase preserving amplitude regeneration

We carry out a detailed experimental characterization of a four-wave mixing based amplitude limiter in highly nonlinear fiber based on the Bessel-like power transfer characteristics and highlight trade-offs for phase preserving capabilities

Optical predistortion enabling phase preservation in optical signal processing demonstrated in FWM-based amplitude limiter

We propose and demonstrate a technique to obtain phase preservation in optical processing which is suitable for many four-wave mixing (FWM) based processing devices, provided they may be modified to incorporate two conjugating FWM stages. It functions by using a first conjugating nonlinear stage to predistort the signal using self-phase modulation (SPM) such that when the signal undergoes further SPM in a second conjugating FWM stage, the two SPM contributions negate each other, resulting in phase preserving output. In this work, we use the second stage to perform amplitude squeezing through parametric gain saturation and characterise the scheme by regenerating a QPSK signal contaminated with broadband amplitude noise. Experimental analysis of the system with and without predistortion is provided and phase preserving operation using the proposed scheme is confirmed

Multi-channel all-optical signal processing based on parametric effects

Two different experiments that use parametric effects for the processing of multiple signals in a single fiber are reviewed. The first experiment uses optical phase conjugation to mitigate the effects of nonlinearity in transmission, whereas the second uses multiple phase-sensitive amplifiers to regenerate six different channels

Probabilistic coherence, logical consistency, and Bayesian learning: Neural language models as epistemic agents

It is argued that suitably trained neural language models exhibit key properties of epistemic agency: they hold probabilistically coherent and logically consistent degrees of belief, which they can rationally revise in the face of novel evidence. To this purpose, we conduct computational experiments with rankers: T5 models [Raffel et al. 2020] that are pretrained on carefully designed synthetic corpora. Moreover, we introduce a procedure for eliciting a model’s degrees of belief, and define numerical metrics that measure the extent to which given degrees of belief violate (probabilistic, logical, and Bayesian) rationality constraints. While pretrained rankers are found to suffer from global inconsistency (in agreement with, e.g., [Jang et al. 2021]), we observe that subsequent self-training on auto-generated texts allows rankers to gradually obtain a probabilistically coherent belief system that is aligned with logical constraints. In addition, such self-training is found to have a pivotal role in rational evidential learning, too, for it seems to enable rankers to propagate a novel evidence item through their belief systems, successively re-adjusting individual degrees of belief. All this, we conclude, confirms the Rationality Hypothesis, i.e., the claim that suitable trained NLMs may exhibit advanced rational skills. We suggest that this hypothesis has empirical, yet also normative and conceptual ramifications far beyond the practical linguistic problems NLMs have originally been designed to solve